skip to main content
10.1145/1276958.1277271acmconferencesArticle/Chapter ViewAbstractPublication PagesgeccoConference Proceedingsconference-collections
Article

Evolving controllers for simulated car racing using object oriented genetic programming

Published: 07 July 2007 Publication History

Abstract

Several different controller representations are compared on anon-trivial problem in simulated car racing, with respect tolearning speed and final fitness. The controller representations arebased either on Neural Networks or Genetic Programming, and alsodiffer in regards to whether they allow for stateful controllers orjust reactive ones. Evolved GP trees are analysed, and attempts aremade at explaining the performance differences observed.

References

[1]
A. Agapitos and S. M. Lucas. Evolving a statistics class using object oriented evolutionary programming. In Proceedings of the 10th European Conference on Genetic Programming, 2007.
[2]
E. Kirshenbaum. Genetic programming with statically scoped local variables. Technical Report HPL-2000-106, Hewlett Packard Laboratories, Palo Alto, 11 Aug. 2000.
[3]
J. Koza. Genetic Programming II: automatic discovery of reusable programs. MIT Press, Cambridge, (1994).
[4]
J. R. Koza, D. Andre, F. H. Bennett III, and M. Keane. Genetic Programming 3: Darwinian Invention and Problem Solving. Morgan Kaufman.
[5]
R. Poli and W. B. Langdon. On the ability to search the space of programs of standard, one-point and uniform crossover in genetic programming. Technical report, University of Birmingham (1998).
[6]
A. Teller. The evolution of mental models. In KE. Kinnear, Jr., editor, Advances in Genetic Programming, chapter 9, pages 199--219. MIT Press, 1994.
[7]
J. Togelius and S. M. Lucas. Evolving controllers for simulated car racing. In Proceedings of the Congress on Evolutionary Computation, 2005.
[8]
J. Togelius and S. M. Lucas. Arms races and car races. In Proceedings of PPSN IX. Springer, 2006.
[9]
J. Togelius and S. M. Lucas. Evolving robust and specialized car racing skills. In Proceedings of the IEEE Congress on Evolutionary Computation, 2006.

Cited By

View all
  • (2023)Evolutionary Computation and the Reinforcement Learning ProblemHandbook of Evolutionary Machine Learning10.1007/978-981-99-3814-8_4(79-118)Online publication date: 2-Nov-2023
  • (2020)Playing Mega Man II with Neuroevolution2020 IEEE Symposium Series on Computational Intelligence (SSCI)10.1109/SSCI47803.2020.9308303(2359-2364)Online publication date: 1-Dec-2020
  • (2020)Analysis of Feed Forward Neural Network Autonomous Driving Agents in Games2020 6th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS)10.1109/ICSPIS51611.2020.9349532(1-6)Online publication date: 23-Dec-2020
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation
July 2007
2313 pages
ISBN:9781595936974
DOI:10.1145/1276958
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 July 2007

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. evolutionary computer games
  2. evolutionary robotics
  3. genetic programming
  4. homologous uniform crossover
  5. neural networks
  6. object-oriented
  7. subtree macro-mutation

Qualifiers

  • Article

Conference

GECCO07
Sponsor:

Acceptance Rates

GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;
Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)2
  • Downloads (Last 6 weeks)0
Reflects downloads up to 16 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2023)Evolutionary Computation and the Reinforcement Learning ProblemHandbook of Evolutionary Machine Learning10.1007/978-981-99-3814-8_4(79-118)Online publication date: 2-Nov-2023
  • (2020)Playing Mega Man II with Neuroevolution2020 IEEE Symposium Series on Computational Intelligence (SSCI)10.1109/SSCI47803.2020.9308303(2359-2364)Online publication date: 1-Dec-2020
  • (2020)Analysis of Feed Forward Neural Network Autonomous Driving Agents in Games2020 6th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS)10.1109/ICSPIS51611.2020.9349532(1-6)Online publication date: 23-Dec-2020
  • (2019)Simulation-Based OptimizationNatural Computing for Simulation-Based Optimization and Beyond10.1007/978-3-030-26215-0_3(31-57)Online publication date: 27-Jul-2019
  • (2018)On the effect of function set to the generalisation of symbolic regression modelsProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3205651.3205773(272-273)Online publication date: 6-Jul-2018
  • (2018)Generating beginner heuristics for simple texas hold'emProceedings of the Genetic and Evolutionary Computation Conference10.1145/3205455.3205601(181-188)Online publication date: 2-Jul-2018
  • (2018)Machine learning in digital gamesArtificial Intelligence Review10.1007/s10462-009-9112-y29:2(123-161)Online publication date: 28-Dec-2018
  • (2018)Designing high-level decision making systems based on fuzzy if–then rules for a point-to-point car racing gameSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-009-0448-714:5(517-528)Online publication date: 29-Dec-2018
  • (2017)Ahura: A Heuristic-Based Racer for the Open Racing Car SimulatorIEEE Transactions on Computational Intelligence and AI in Games10.1109/TCIAIG.2016.25656619:3(290-304)Online publication date: Sep-2017
  • (2017)Regularised gradient boosting for financial time-series modellingComputational Management Science10.1007/s10287-017-0280-y14:3(367-391)Online publication date: 23-May-2017
  • Show More Cited By

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media